Synthetic AI Training Data Providers

A synthetic data generation platform that produces photorealistic, multi-modal training datasets (RGB, depth, thermal, LiDAR, radar) with automatically generated pixel-perfect annotations across unlimited scene variations, delivering ready-to-use labeled datasets for training computer vision models without real-world data collection.

Synth is Pleias's synthetic data generation platform that turns domain documents into high-quality, structured synthetic training datasets—including Q&A pairs, reasoning chains, and multilingual data—with automatic PII removal, schema validation, and full pipeline observability, available via on-premise deployment or API.

A cloud-native, physics-based synthetic data generation platform that produces sensor-accurate, automatically annotated datasets across multiple modalities (RGB, NIR, infrared, LiDAR, radar, thermal) for training and validating AI perception models in ADAS, autonomous driving, in-cabin monitoring, and defense applications.

An end-to-end synthetic data generation and verification platform for LLM fine-tuning teams that produces execution-verified, benchmark-targeted coding datasets with PII stripping, differential-privacy certification, and signed data lineage—delivered via dashboard or REST API with a model performance guarantee.

Synthetic, scenario-driven dataset packs and private generators for AI training, agent evaluation, analytics demos, and simulation—delivering 100% synthetic data in JSONL and Parquet formats across industry verticals including finance, healthcare, operations, and AI agent training, with no real customer data ever used.

A flat-file synthetic data generation platform that uploads any tabular dataset and generates millions of statistically accurate, privacy-preserving synthetic rows in under a minute, purpose-built for ML training pipelines, QA fixture generation, and analytics workloads that cannot use real customer data.